AI & Data-Driven Product Solutions
At CQUBE Solutions, we empower businesses to unlock the true potential of their data by building AI-powered, data-driven product solutions that enhance decision-making, automate operations, and deliver personalized user experiences. From intelligent automation to predictive analytics and machine learning models, we design and implement solutions that turn raw data into strategic assets.
Our expertise lies in combining domain knowledge, AI technologies, and custom software engineering to build products that are not just smart—but transformational.
Our Offerings Include
Smart features such as recommendation engines, natural language processing (NLP), and computer vision are seamlessly integrated into web and mobile applications, enhancing user experience and functionality.
Build, train, and deploy ML models to forecast trends, optimize operations, and reduce business risks.
End-to-end data pipeline development, including data collection, cleaning, transformation, and dashboard creation using Power BI, Tableau, and custom platforms.
Deploy intelligent virtual assistants to streamline customer support and internal processes.
Use generative AI and RPA to automate repetitive tasks, accelerate workflows, and improve accuracy.
Case Study: AI-Powered Inventory Optimization for an E-Commerce Platform
Client Overview
A mid-sized e-commerce company based in North America, offering a wide range of fashion and lifestyle products. The client faced frequent challenges with stock outs and overstocking, which affected customer satisfaction and increased operational costs.
The Challenge
- Lack of accurate demand forecasting
- Manual inventory management leading to inefficiencies
- No insights into seasonality or customer purchase behavior
- Overstock leading to warehousing issues and understock causing sales loss
Our Solution
CQUBE Solutions developed a custom AI-powered inventory optimization engine, integrated into the client’s existing ERP and e-commerce platform.
Key Features Implemented
Machine learning algorithms trained on 3 years of historical sales data, seasonality, promotions, and regional trends
Real-time alerts and reorder thresholds based on predictive insights
Clustered users by purchase patterns to align inventory with demand
Interactive visualizations showing low-stock alerts, slow-moving items, and forecast accuracy
Technologies Used
- ML Models: XGBoost, Prophet (for time-series forecasting)
- Backend: Python, Pandas, FastAPI
- Data Storage: AWS Redshift, S3
- Visualization: Power BI, custom dashboard using React.js
- Integration: Shopify API, custom ERP APIs
Results & Impact
- 35% reduction in inventory holding costs
- 25% improvement in product availability and order fulfilment rates
- 20% increase in customer satisfaction due to reduced stock outs
- Improved decision-making with real-time visibility into inventory trends
Thanks to Cqube Solutions, we now have complete control and visibility over our inventory. Their AI model helped us reduce waste, improve customer service, and grow smarter with every sale
